code: def test_dist_backward(self):
      if self.rank != 0:
          return
  
      @torch.jit.script
      def dist_backward_script(context_id: int, loss: torch.Tensor):
          dist_autograd.backward(context_id, [loss])
  
      FileCheck().check("dist_backward").run(
          str(dist_backward_script.graph)
      )
      with dist_autograd.context() as context_id:
          t1 = torch.rand(3, 3, requires_grad=True)
          t2 = torch.rand(3, 3, requires_grad=True)
          dst_worker_name = worker_name(
              (self.rank + 1) % self.world_size
          )
          loss = rpc.rpc_sync(
              dst_worker_name, torch.add, args=(t1, t2)
          ).sum()
          dist_backward_script(context_id, loss)
  
file_path: pytorch/torch/testing/_internal/distributed/rpc/jit/dist_autograd_test.py
imports: from typing import Dict, Tuple
  import torch
  import torch.distributed.autograd
  import torch.distributed.rpc
  from torch import Tensor
  from torch.distributed.rpc import rpc_async
  from torch.testing import FileCheck
  from torch.testing._internal.dist_utils import dist_init, worker_name
  from torch.testing._internal.distributed.rpc.rpc_agent_test_fixture import RpcAgentTestFixture
label_desc: Use image node_id 2 for calling the JitDistAutogradTest obj's underlying member method code with example usage: obj.test_dist_backward() without return types